Sort by
Refine Your Search
-
functional theory) and high-performance computing. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to
-
. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
-
, heterogeneous catalysis, electrocatalysis, sustainable energy, and machine learning. We develop and apply electronic structure theory, i.e., density functional theory and correlated wavefunction theory, to design
-
limited to brain imaging (broadly defined), electrophysiology, genotyping, brain stimulation (tES, TMS), computational modeling and/or machine learning. For all our projects, we seek post-doctoral
-
, electrocatalysis, sustainable energy, and machine learning. We develop and apply electronic structure theory, i.e., density functional theory and correlated wavefunction theory, to design heterogeneous catalysts
-
), electrophysiology, genotyping, brain stimulation (tES, TMS), computational modeling and/or machine learning. For all our projects, we seek post-doctoral researchers who aim to take leading roles in projects
-
), psychophysics (in person and online), computational modeling, and machine learning to arbitrate among competing hypotheses about the neural mechanisms of conscious awareness. This project is part of
-
Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific
-
About the Opportunity SUMMARY The lab of Professor Albert-László Barabási is looking for Postdoctoral Research Associates in the area of network science, nutrition, biological networks, machine
-
. CV with a list of publications. Names and contact details for 2 references. QUALIFICATIONS PhD in network science, physics, big data, behavior modeling, urban science, complex systems, machine learning